Slides Section¶

Motivate Inc. Customers: Deeper Understanding¶

Created by: Adel Ahmed

Jan 2022

OUTLINE¶

  1. Executive Summary
  2. Introduction
  3. Methodology
  4. Results
    • Visualization – Charts
  5. Discussion
  6. Findings & Implications
  7. Conclusion
  8. Appendix
Section 1¶

EXECUTIVE SUMMARY¶

  • Identify how annual members and casual riders differ
  • Recommendations for the new marketing strategy based on findings
Section 2¶

INTRODUCTION¶

The head of Marketing believes that maximizing the number of annual members will be key to future growth.
Moreno has set a clear goal: Design marketing strategies aimed at converting casual riders into annual members.

Marketing team are interested in analyzing the Cyclistic historical bike trip data to identify trends
The question to answer in this Analysis is: How do annual members and casual riders use Cyclistic bikes differently?
Also recommendations will be provided based on the finding of this Analysis

Description of the dataset

No. Column Description Data Type Category
1 Ride_Id Customer Unique ID String Nominal
2 Rideable_Type The type of bike customer used for the trip String Nominal
3 Started_At The date and time when the trip started DateTime Discrete
4 Ended_At The date and time when the trip ended DateTime Discrete
5 Start_Station_Name Name of the station where the trip started String Nominal
6 Start_Station_Id ID of the station where the trip started String Nominal
7 End_Station_Name Name of the station where the trip ended String Nominal
8 End_Station_Id ID of the station where the trip ended String Nominal
9 Start_Lat Latitude value where the trip have started expressed in decimal degrees Float Contiuous
10 Start_Lng Longitude value where the trip have started expressed in decimal degrees Float Contiuous
11 End_Lat Latitude value where the trip have ended expressed in decimal degrees Float Contiuous
12 End_Lng Longitude value where the trip have ended expressed in decimal degrees Float Contiuous
13 Member_Casual Classification of Customers: Customers who purchase single-ride or full-day passes are referred to as casual. Customers who purchase annual memberships referred to as members String Nominal
Section 3¶

METHODOLOGY¶

  • Collecting Data from the publicly avaialbe dataset
  • Acquring location data from publicly available API
  • Examining all data to conduct the analysis
  • Exploring the data through statistics and visualization
  • Listing the findings and insights from the analysis
  • Recommendations for the Marketing Team
Section 4¶

RESULTS¶

  • Exploratory Data Analysis Results

Exploratory Data Analysis Results¶

Out[113]:
Out[173]:
Section 5¶

DISCUSSION¶

Members drive faster on average while casual riders tend to ride for longer periods of time

Section 6¶

Findings & Implications¶

  1. Time-Related Recommendation: ensuring the demand for bicycles are met and having availability also during peak times:

    • Morning and afternoon for the day
    • Weekends for the week
    • Summer and fall for the year

  2. Location Related Recommendation: 6 Chicago suburbs being the most visited by riders, in those suburbs where the offering of bikes and advertisement should take place:

    • Near North Side
    • Lincoln Park
    • Lake View
    • Loop
    • Near West Side
    • West Town

  3. Equipment Related Recommendation: since the members tend to use the bicycles for shorters period and faster travel times, introducing more electric bikes with better mileage and higher speed for members will keep the current members happy and spark interest for casual who need quick rides, not to forget it is less physical,environment friendly and also can help in having more riders to explore the other suburbs of the city

Section 7¶

CONCLUSION¶

Summer campaign targeted at high demand areas with new and faster bycicles options should be the new strategy for marketing.

Section 8¶

APPENDIX¶

More information can be found at My Portfolio

Thank you¶

Looking forward to seeing you agian.